The present invention relates to the operation of an ethylene plant. In particular, the present invention relates to determining when the ethylene plant is deviating from normal operation.
In the petrochemical industry, an Olefins Recovery Train (ORT) is a very important process for an ethylene plant. The ORT purifies ethylene and propylene and also recovers by-products of the olefins production plant. Due to the complicated dynamic nature and cryogenic portions of the ORT, abnormal process operations can easily result from many root problems that cause the ORT operation to deviate from the normal operating state. Abnormal operations of the ORT can have significant economic implications and, in many cases, can stop production. These abnormal situations can cause lost production, equipment damage, environmental emissions, injuries and fatalities. A primary job of the console operator is to identify the cause of the abnormal situation and execute compensatory or corrective actions in a timely and efficient manner.
The current commercial practice is to use advanced process control applications to automatically adjust the process in response to minor process disturbances. For moderate to severe abnormal operations, the current practice is to rely on human process intervention. And for very severe abnormal operations, the current practice is to use automatic emergency shutdown (ESD) systems that can have substantial economic consequences for the process equipment.
Currently, the console operator is notified of an abnormal condition via process alarms. These alarms are triggered when key process measurements (temperatures, pressures, flows, levels, compositions, valve positions, etc.) violate a pre-defined set of operating ranges. These operating ranges are often static values from initial designs or frequently adjusted values by console operators to envelop important operating regions. For highly integrated processes, such as ORT, the alarm system effectiveness is an often difficult balance of providing timely alarms during normal operation (early warning) and preventing “alarm floods” during abnormal operation (risk of high priority information being missed). Thus, the current notification technology is challenged to provide sufficient early notifications while generating an acceptable rate (near zero) of false notifications to ensure the alarm system remains effective during severe abnormal operation.
There can be many thousands of process measurements that cover the operation of a typical ORT, of which hundreds are considered key to normal operation. In addition, each process measurement can have as many as 15 different alarms being configured. Under a conventional Distributed Control System (DCS) like Honeywell's TDC3000, the operator must survey this list of sensors and its trends, compare them with mental knowledge of normal ORT operation, and discover the potential problems early enough to intervene before significant disruptions can occur. Due to the very large number of sensors in an operating ORT, abnormalities can be easily missed. With the current DCS based monitoring technology, the only automated detection assistance an operator has is the DCS alarm system which is based on the alarming of each sensor when it violates predetermined limits. Due to the complexity of an ORT, this type of notification often comes in too late to allow the operator to have sufficient time to take preventive action to mitigate a problem. Over-use of the alarm system for early detection can have even worse consequences. The alarms become an annoyance to the operator during normal operation and the operator ignores the alarm system. During abnormal conditions, the operator becomes flooded with alarms and misses critical information. The present invention provides a more effective notification to the operator of the ORT.